There are obviously a variety of choices open to you: a spreadsheet plug-in may be appropriate if you are only focused on general ledger reporting and do not have concerns over security or compliance. You might also suppose that this is a low-cost option, though we would argue that the remediation required, the additional audit fees and the lack of repeatability means that this is a false economy and that this approach will end up costing you more in the long term. A second use case would be where you already have a financial reporting solution installed, when the add-on facilities for purposes such as business intelligence are likely to be your major focus. In this case an Oracle based solution is likely to be as good as anything else.

There are obviously a variety of choices open to you: a spreadsheet plug-in may be appropriate if you are only focused on general ledger reporting and do not have concerns over security or compliance. You might also suppose that this is a low-cost option, though we would argue that the remediation required, the additional audit fees and the lack of repeat-ability means that this is a false economy and that this approach will end up costing you more in the long term. A second use case would be where you already have a financial reporting solution installed, when the add-on facilities for purposes such as business intelligence are likely to be your major focus. In this case an Oracle-based solution is likely to be as good as anything else.

Surviving and thriving amid the global, digital shopping revolution, in which consumers fluidly browse and buy from their smartphones, computers and in store, calls for a supply-chain makeover.
Pressed to offer consumers fast, flexible and even free product fulfillment and delivery in an omnichannel retail landscape, a crowdsourced, collaborative model is taking shape. Traditional roles are blurring as logistics companies, manufacturers and retailers work to meet the growing on-demand economy via the adoption of business intelligence supply chain technologies.

If your business is like most, you are grappling with data storage. In an annual Frost & Sullivan survey of IT decision-makers, storage growth has been listed among top data center challenges for the past five years.2 With businesses collecting, replicating, and storing exponentially more data than ever before, simply acquiring sufficient storage capacity is a problem.
Even more challenging is that businesses expect more from their stored data. Data is now recognized as a precious corporate asset and competitive differentiator: spawning new business models, new revenue streams, greater intelligence, streamlined operations, and lower costs. Booming market trends such as Internet of Things and Big Data analytics are generating new opportunities faster than IT organizations can prepare for them.

Selling isn’t about blasting prospects with generic cold emails. That mile wide and inch deep approach might have worked in 1998, but it’s not going to cut it anymore. You need to connect with your prospects on a level that shows you understand their business and their needs. Sales intelligence is the ultimate must-have in your modern, account based sales toolkit because it allows you to learn more about your prospect and, in turn, sell more successfully.Just like you wouldn’t go on a blind date without a little online stalkingresearch, you shouldn’t call a prospect without understanding who they are, where they work, and what matters to them.At the end of the day, when you understand who you’re selling to, you can solve their problems better. This creates happier customers and prospects who trust you, which leads to more closed deals and more fist bumps all around.

Location analytics is the process of
integrating geographical data into business intelligence (BI) and analytics-led decision
making. Location analytics creates meaningful insight from relationships found in
geospatial data to solve a broad variety of business and social problems.
Location data is found everywhere – with an item or a device, in a conversation or
behavior, in machines or sensors, tied to a customer or competitor, attached to a
database record or recorded from vehicles or other moving objects. Organizations
want to take advantage of location data to improve decisions, create better customer
engagement and experiences, reduce risks and automate business processes.

Healthcare and Life Sciences organizations are adopting cloud-based workloads at a significant pace. A 2017 HIMSS study found that 65% of Healthcare organizations were using cloud-based services, and nearly 88% of those organizations were utilizing Software-as-a-Service (SaaS) solutions, which have become the preferred deployment method for many clinical application vendors.
This eBook highlights advantages of using AWS to create and maintain cloudbased Next-Gen BI Solutions for Healthcare and Life Sciences organizations. This includes use cases from diverse organizations that have utilized AWS and APN Partners to manage and analyze data, and to discover insights otherwise obscured by the sheer volume of available information. Solutions from APN Partners can help your organization take the next step in building robust processes for making data-driven decisions that improve patient care, organizational processes, and innovative product development efforts.

SQL is a critical skill for business intelligence. From accessing to transforming to reporting on data, SQL gives you the power to get the job done. It can help you discover exactly how your company is performing, what your customers are doing, or how people have reacted to your marketing campaigns.
Unfortunately, while SQL can tell you what has happened, it can’t tell you what will happen. What if you have questions like:
• How valuable is a lead based on company attributes and their behavior on our website? • How much MRR will we generate in the next 30 days? • Which customers are likely to churn next month?

Today's artifical intelligence (AI) solutions are not sentient in the manner popularized in science fiction by scores of self-aware and typically nefarious androids. Even so, the ability to arm such systems with the ability to directly sense and respond to their in situ environment is critical. Why? In the future, our experiences will be smart, intuitive and informed by analytics that are not seen
but felt via new business, personal and operational engagement models. Enabling this interaction requires AI applications that can sense, analyze and respond to their environment in an intelligent
and interactive manner. Without requiring the end user to write, understand or interpret code.
“Sensitive” artificial intelligence enables:
• More productive use of expanded (big, often unstructured) information sources
• Intuitive man-machine interactions (no code-speak here!)
• Adaptive, immersive experiences and environments
As frequently touted on the nightly news, AI’s popularity is clear. Ho

With decisions riding on the timeliness and quality of analytics, business stakeholders are
less patient with delays in the development of new applications that provide reports, analysis,
and access to diverse data itself. Executives, managers, and frontline personnel fear that
decisions based on old and incomplete data or formulated using slow, outmoded, and limited
reporting functionality will be bad decisions. A deficient information supply chain hinders quick
responses to shifting situations and increases exposure to financial and regulatory risk—putting
a business at a competitive disadvantage. Stakeholders are demanding better access to data,
faster development of business intelligence (BI) and analytics applications, and agile solutions in
sync with requirements.

Business intelligence has come a long way ? from assistance with report generation to self-service platforms for discovery and analytical
insight. As technological capabilities and business aptitude with information continue to advance, the next generation of BI will be even
more capable and valuable to the enterprise. To discuss today’s success factors and tomorrow’s opportunities, IIA spoke with Rick Styll,
Senior Manager, Visual Analytics Product Management at SAS, and Tapan Patel, Principal Product Marketing Manager at SAS.

Known for its industry-leading analytics, data management and business intelligence solutions, SAS is focused on helping organizations use data and analytics to make better decisions, faster. The combination of self-service BI and analytics positions you for improved productivity and smarter business decisions. So you can become more competitive as you use all your data to take better actions. Instead of depending on hunch-based choices, you can make decisions that are truly rooted in discovery and
analytics. And you can do it through an interface that anyone can use.
At last, your business users can get close enough to the data to manipulate it and draw their own reliable, fact-based conclusions. And they can do it in seconds or minutes, not hours or days.
Equally important, IT remains in control of data access and security by providing trusted data sets and defined processes that promote the valuable, user-generated content for reuse and consistency. But, they are no longer forced

These emerging technologies and solutions certainly are not unique to financial services. But Stewart, a business director of security intelligence solutions within the SAS Security Intelligence
Practice, sees particular interest and application in AML circles.
"There remain a good number of manual processes within financial crimes departments in financial institutions, and AI can help automate some of those rote tasks such as document review or alert triage," he says. "Due to investments in technology, there is a lower barrier of entry for midsized institutions. "And finally, there's this anxiety over the unknown - those risks they are not able to detect, that may be hidden using traditional techniques - so they're hoping that more advanced, unsupervised learning techniques can be used to identify those edge cases or behaviors that are out of norm." In an interview about analytics and the AML paradigm shift, Stewart discusses:
• The new industry intrigue with artificial intelligence a

Did you know that by 2020, 50% of analytic queries will be generated using search, natural-language processing or voice, or will be automatically generated?
Read the Gartner report Technology Insight for Modern Analytics and Business Intelligence Platforms and find out how to meet the time-to-insight demands of today's competitive business environment. Learn how to:
• Determine when to use existing, traditional BI technologies versus modern analytics and BI
• Broaden data access beyond relational systems
• Adopt new approaches to data modeling

Advanced Technology is having a growing impact on our everyday lives. Adoption of advanced technologies and virtual assistants such as Amazon Echo and Google Home are becoming more mainstream in homes. Meanwhile organizations worldwide are increasingly looking at how to implement similar technologies to improve productivity, speed workflows, and increase collaboration among employees, business partners, and even customers.
To date, little is known about perceptions of technologies such as artificial intelligence (AI) and virtual assistants in the workplace and how they will impact how we work in the future.

Improved availability of data and new technologies that use it are disrupting our lives, influencing the way we interact with other, and the way we gather and consume information to make decisions. Businesses too are living in a time of continuous technological upheaval. The application of key technologies such as Machine Learning and Artificial Intelligence and Optimization, are fundamentally changing the manner in which businesses make decisions.
This paper is your first step in understanding:
• how you can leverage and operationalize analytics in your everyday business processes
• improve customer relationships
• grow revenue in an increasingly competitive world

Transform Your Business with Artificial Intelligence (AI)
AI is on the verge of broad adoption, and Mobile will be at the forefront of this digital transformation through the use of intelligent chatbots!
Introducing Oracle Mobile Cloud, Enterprise
Learn about Oracle’s new Intelligent Bots platform and check out the chatbot demo
Listen to Oracle's Suhas Uliyar and Exelon's Rajesh Kumar Thakur discuss how AI is impacting how customers interact with businesses
Learn of the new Customer Experience Analytics capabilities for web, mobile, and chatbots

Data. It seems to be everywhere today and yet we can never get
enough of it. But as it turns out, a lack of data isn’t our problem
-- our problem is the difficulty piecing together, understanding and
finding the story in all the data that’s in front of us.
In software testing in particular, the need for consolidated,
meaningful test metrics has never been higher. As both the pace of
development and the cost of delivering poor quality software
increase, we need these metrics to help us test smarter, better and
faster.
Fortunately, business intelligence now exists to make this goal a
reality. The analytics these tools provide can help drive efficient
and effective testing by providing teams with insight on everything
from testing quality and coverage to velocity and more. And this
knowledge can position the QA team as trusted experts to advise
the entire software development team on steps that can ensure a
better quality end result.

Healthcare and Life Sciences organizations are using data to generate knowledge that helps them provide better patient care, enhances biopharma research and development, and streamlines operations across the product innovation and care delivery continuum. Next-Gen business intelligence (BI) solutions can help organizations reduce time-to-insight by aggregating and analyzing structured and unstructured data sets in real or near-real time.
AWS and AWS Partner Network (APN) Partners offer technology solutions to help you gain data-driven insights to improve care, fuel innovation, and enhance business performance.
In this webinar, you’ll hear from APN Partners Deloitte and hc1.com about their solutions, built on AWS, that enable Next-Gen BI in Healthcare and Life Sciences.
Join this webinar to learn:
How Healthcare and Life Sciences organizations are using cloud-based analytics to fuel innovation in patient care and biopharmaceutical product development.
How AWS supports BI solutions f

Few topics garner more headlines today than artificial intelligence, and for good reason. Despite the fact tech luminaries can’t seem to agree if it’s the world’s greatest existential threat or saviour, there is little debate about its ability to fundamentally transform everyday life and the business models that support it. As Dr. Anastassia Lauterbach, Board member of Dun & Bradstreet, recently put it, “The internet disrupted 20% of all business models. Artificial intelligence will disrupt the remaining 80%.”

Whether you’re onboarding new customers, cross- or up-selling, getting your supply chain or logistics right, or even collecting unpaid debt, making the best choice of decisions means weighing not just what’s right for your department – but what is best for the business overall. Not to mention what is optimal for your customers and partners.
And let’s face it, even with the availability of business intelligence and other analytic tools, it’s hard to know what constitutes the right actions to take in an era where Big Data consistently throws you curveballs. Prescriptive Analytics can help – but for most organizations, there are more questions and concerns than answers about how to implement it successfully.
Read our white paper on how Prescriptive Analytics can transform your business decisions and actions – leveraging your existing analytics investment and organizational DNA while helping you drive transparency, customer experience, and profits

Analyst firm, Enterprise Strategy Group, examines how companies can leverage cloud-based data lakes and self-service analytics for timely business insights that weren’t possible until now.
And learn how IBM Cloud Object Storage, as a persistent storage layer, powers analytics and business intelligence solutions on the IBM Cloud.
Complete the form to download the analyst paper.